Various imaging techniques have been employed for detecting and locating cancerous tumors in body tissue. For example, X-ray and ultrasound imaging techniques are commonly utilized in screening for breast cancer. X-ray mammography is the most effective current method for detecting early stage breast cancer. X-ray mammography, however, suffers from relatively high false positive and false negative rates, requires painful breast compression, and exposes the patient to low levels of ionizing radiation. Microwave based imaging methods have been proposed for use in imaging of breast tissue and other body tissues as an alternative to current ultrasound and X-ray imaging techniques. Microwave imaging does not require breast compression, does not expose the patient to ionizing radiation, and can be applied at low power levels. Microwave-based imaging, such as microwave tomography and radar imaging, exploits the dielectric properties contrast between normal and malignant tissue.
As an example, recent theoretical and experimental laboratory research has established the feasibility of ultrawideband (UWB) microwave radar imaging for early stage breast cancer detection. UWB microwave radar imaging is based on transmitting short-duration microwave signals into the breast using an array of antennas placed near the breast surface and then measuring the scattered microwave signals. Scattering arises due to the significant contrast in the dielectric properties that exists at microwave frequencies between normal fatty and malignant breast tissue. The temporal and spectral characteristics of the measured scattered signals are used by UWB microwave radar imaging algorithms to identify the presence and location of malignant lesions.
UWB radar signal processing algorithms for detecting and imaging breast lesions typically assume a propagation model for a homogeneous breast medium. The actual scatter, however, is acquired from heterogeneous breast tissue. Numerical and experimental laboratory studies have shown that more accurate tumor localization is achieved when the material parameters in the propagation model represent the spatial average of the properties of the actual, heterogeneous breast tissue. The average properties, however, are unknown a priori and are expected to vary from patient to patient. As a result, a calibration step that yields estimates of the patient-specific breast tissue averages is a key component of a UWB microwave radar imaging system.
Techniques have been developed for estimating the dielectric and conductive distributions in a region of space using measurements of the scattered microwave signals. The estimation problem, however, is typically nonlinear and ill-posed. Iterative inverse scattering algorithms that sequentially update the estimated spatial distributions have been employed to obtain a voxelized approximation of the actual spatial distribution of electromagnetic material properties after a sufficient number of iterations. The ill-posedness of this problem increases as the resolution of the reconstructed profile increases because the number of unknowns increases. The nonlinearity and ill-posedness of the inverse problem also tend to increase as the frequency of the probing excitation increases. Thus, what is needed is a system and a method for estimating average properties that does not suffer from the nonlinearity and ill-posedness of the full inverse scattering problem. Ideally, this system and a method are robust to various levels of knowledge of the properties of the skin layer surrounding the underlying breast tissue.